Skip to main content

Differences Between BPM and ACM Models for Process Execution

  • Conference paper
  • First Online:
Business Modeling and Software Design (BMSD 2018)

Abstract

As the demand for the modeling of knowledge intensive processes grows, so does the necessity to support this task by appropriate models. Adaptive Case Management (ACM) was proposed as appropriate, whereas still confined mostly to theoretical work. This paper compares the execution of BPM process models to ACM models by applying agent based simulations to different processes based on support case handling. The simulation tools applied to the ACM process models were developed in the course of this work. The greater flexibility of ACM models is found to be more effective in processing executions with competent knowledge workers. Another key observation is the possible improvement of average case duration due to parallelization effects.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Chinosi, M., Trombetta, A.: BPMN: an introduction to the standard. Comput. Stand. Interfaces 34, 124–134 (2012)

    Article  Google Scholar 

  2. Işik, Ö., Mertens, W., Van den Bergh, J.: Practices of knowledge intensive process management: quantitative insights. Bus. Process Manag. J. 19, 515–534 (2013)

    Article  Google Scholar 

  3. Pesic, M., van der Aalst, W.M.P.: A declarative approach for flexible business processes management. In: Eder, J., Dustdar, S. (eds.) BPM 2006. LNCS, vol. 4103, pp. 169–180. Springer, Heidelberg (2006). https://doi.org/10.1007/11837862_18

    Chapter  Google Scholar 

  4. Slaats, T.: Flexible Process Notations for Cross-organizational Case Management Systems (2015)

    Google Scholar 

  5. Desel, J., Erwin, T.: Modeling, simulation and analysis of business processes. In: van der Aalst, W., Desel, J., Oberweis, A. (eds.) Business Process Management. LNCS, vol. 1806, pp. 129–141. Springer, Heidelberg (2000). https://doi.org/10.1007/3-540-45594-9_9

    Chapter  Google Scholar 

  6. Swenson, K.D.: Mastering the Unpredictable: how Adaptive Case Management Will Revolutionize the Way That Knowledge Workers get Things Done. Meghan-Kiffer Press, Tampa (2010)

    Google Scholar 

  7. Motahari-Nezhad, H.R., Swenson, K.D.: Adaptive case management: overview and research challenges. In: 15th Conference on Business Informatics (CBI) 2013, pp. 264–269. IEEE (2013)

    Google Scholar 

  8. Dorst, W.: Adaptive-Case-Management: Leitfaden und Nachschlagewerk (2013)

    Google Scholar 

  9. Hauder, M., Pigat, S., Matthes, F.: Research challenges in adaptive case management: a literature review. In: 18th International Enterprise Distributed Object Computing Conference Workshops and Demonstrations 2014. IEEE (2014)

    Google Scholar 

  10. Fischer, L. (ed.): How Knowledge Workers Get Things Done: Real-World Adaptive Case Management. Future Strategies, Lighthouse Point (2012)

    Google Scholar 

  11. Jansen-Vullers, M., Netjes, M.: Business process simulation–a tool survey. In: Workshop and Tutorial on Practical Use of Coloured Petri Nets and the CPN Tools, Aarhus, Denmark (2006)

    Google Scholar 

  12. Pichler, P., Weber, B., Zugal, S., Pinggera, J., Mendling, J., Reijers, H.A.: Imperative versus declarative process modeling languages: an empirical investigation. In: Daniel, F., Barkaoui, K., Dustdar, S. (eds.) BPM 2011. LNBIP, vol. 99, pp. 383–394. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-28108-2_37

    Chapter  Google Scholar 

  13. Debois, S., Hildebrandt, T., Marquard, M., Slaats, T.: The DCR graphs process portal. In: Business Process Management Forum 2016 (2016)

    Google Scholar 

  14. Hildebrandt, T.T., Mukkamala, R.R.: Declarative event-based workflow as distributed dynamic condition response graphs. Electron. Proc. Theor. Comput. Sci. 69, 59–73 (2011)

    Article  Google Scholar 

  15. Hildebrandt, T., Marquard, M., Mukkamala, R.R., Slaats, T.: Dynamic condition response graphs for trustworthy adaptive case management. In: Demey, Y.T., Panetto, H. (eds.) On the Move to Meaningful Internet Systems: OTM 2013 Workshops, pp. 166–171. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-41033-8_23

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Alexander Adensamer .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG, part of Springer Nature

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Adensamer, A., Rueckel, D. (2018). Differences Between BPM and ACM Models for Process Execution. In: Shishkov, B. (eds) Business Modeling and Software Design. BMSD 2018. Lecture Notes in Business Information Processing, vol 319. Springer, Cham. https://doi.org/10.1007/978-3-319-94214-8_18

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-94214-8_18

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-94213-1

  • Online ISBN: 978-3-319-94214-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics